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Towards Flexible and Adaptive Human-Robot Collaborations via Event-driven Microservices

Journal
International Conference on Emerging Technologies and Factory Automation (ETFA)
Type
conference paper
Date Issued
2025-09
Author(s)
Ronny Seiger  
DOI
10.1109/ETFA65518.2025.11205740
Abstract
Robotic co-working relies on the perception of the human and the robot's surroundings to ensure safe operations. Building the respective means for sensing into the hardware and software of a robot is expensive and results in inflexible, non-extensible routines that are hardwired into the robot's programming. In this work we investigate the application of modern software architecture principles to this problem. We propose an architecture that relies on event-driven microservices to provide fine-grained access to robots and other machines. Complex event processing (CEP) allows to augment the microservices with advanced reactive behavior by incorporating events from external sensors, process them, and control the machines accordingly. The programming of the CEP applications is facilitated by SQL-like queries that support domain experts with flexibly connecting sensors, specifying their processing, and corresponding actions.
Funding(s)
Software Architectures for Human-Robot Collaborations in Industry 4.X  
Language
English (United States)
Keywords
Software architecture
human-robot collaboration
event processing
microservices
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
IEEE
Pages
4
Event Title
30th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2025)
Event Location
Porto, Portugal
Event Date
9-12 September, 2025
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/123389
Subject(s)

computer science

Division(s)

ICS - Institute of Co...

File(s)
Thumbnail Image

open.access

Name

1_seiger_ronny_poster_A1.pdf

Size

18.33 MB

Format

Adobe PDF

Checksum (MD5)

9256701c4494d97d8bf07fc035e25c49

Thumbnail Image
Name

2025_ETFA_Adaptive_HRC_with_ED_MS.pdf

Size

1.04 MB

Format

Adobe PDF

Checksum (MD5)

841ced9c45fa770cdbddae4128897c02

Support
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